Blog Archives

Hierarchical Loss Reserving with Stan

November 10, 2015
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Hierarchical Loss Reserving with Stan

I continue with the growth curve model for loss reserving from last week's post. Today, following the ideas of James Guszcza I will add an hierarchical component to the model, by treating the ultimate loss cost of an accident year as a random effect. Initially, I will use the nlme R package, just as James did...

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Loss Developments via Growth Curves and Stan

November 3, 2015
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Loss Developments via Growth Curves and Stan

Last week I posted a biological example of fitting a non-linear growth curve with Stan/RStan. Today, I want to apply a similar approach to insurance data using ideas by David Clark and James Guszcza .Instead of predicting the growth of dugongs (sea cows), I would like to predict the growth of cumulative insurance...

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Non-linear growth curves with Stan

October 27, 2015
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Non-linear growth curves with Stan

I suppose the go to tool for fitting non-linear models in R is nls of the stats package. In this post I will show an alternative approach with Stan/RStan, as illustrated in the example, Dugongs: "nonlinear growth curve", that is part of Stan's documentation. The original example itself is taken from OpenBUGS. The data describes the...

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ChainLadder 0.2.2 is out with improved glmReserve function

September 29, 2015
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ChainLadder 0.2.2 is out with improved glmReserve function

We released version 0.2.2 of ChainLadder a few weeks ago. This version adds back the functionality to estimate the index parameter for the compound Poisson model in glmReserve using the cplm package by Wayne Zhang. Ok, what does this all mean? I will run through a couple of examples and look behind the scene of glmReserve....

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Notes from the Kölner R meeting, 18 September 2015

September 22, 2015
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Notes from the Kölner R meeting, 18 September 2015

Last Friday the Cologne R user group came together for the 15th time. Since its inception over three years ago the group evolved from a small gathering in a pub into an active data science community, covering wider topics than just R. Still, R is the link and clue between the different interests. Last Friday's agenda was a...

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Next Kölner R User Meeting: Friday, 18 September 2015

September 15, 2015
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Next Kölner R User Meeting: Friday, 18 September 2015

The 15th Cologne R user group meeting is scheduled for this Friday, 18 September 2015 and we have a full agenda with three talks followed by networking drinks. R in big data pipeline with luigi (Yuki Katoh)R in big data pipeline: Put your awesome R codes into production. Learn how to build...

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Bayesian regression models using Stan in R

September 1, 2015
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Bayesian regression models using Stan in R

It seems the summer is coming to end in London, so I shall take a final look at my ice cream data that I have been playing around with to predict sales statistics based on temperature for the last couple of weeks , , .Here I will use the new brms (GitHub, CRAN) package...

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Visualising the predictive distribution of a log-transformed linear model

August 25, 2015
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Visualising the predictive distribution of a log-transformed linear model

Last week I presented visualisations of theoretical distributions that predict ice cream sales statistics based on linear and generalised linear models, which I introduced in an earlier post.Theoretical distributionsToday I will take a closer look at t...

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Visualising theoretical distributions of GLMs

August 18, 2015
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Visualising theoretical distributions of GLMs

Two weeks ago I discussed various linear and generalised linear models in R using ice cream sales statistics. The data showed not surprisingly that more ice cream was sold at higher temperatures.icecream temp=c(11.9, 14.2, 15.2, 16.4, 17.2, 18.1, 18.5, 19.4, 22.1, 22.6, 23.4, 25.1), units=c(185L, 215L,...

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Generalised Linear Models in R

August 4, 2015
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Generalised Linear Models in R

Linear models are the bread and butter of statistics, but there is a lot more to it than taking a ruler and drawing a line through a couple of points.Some time ago Rasmus Bååth published an insightful blog article about how such models could be described from a distribution centric point of view, instead of...

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